Distance learning

ORDECSYS proposes distance learning sessions on multi-agent decision analysis under uncertainty.

Game theory

This course is an introduction to the Classical Theory of Games for learners who have a background in natural sciences, engineering or social sciences. Its aim is to provide a practical knowledge of the basic concepts of game theory, in particular those related to the solution of non-cooperative games.Game theory provides important paradigms in economics, political science, ecology, control theory. This course lays the foundations on which one will be able to build more advanced Game theory courses, like e.g. Dynamic Games.


  • Introduce learners to the basic concepts of game theory.
  • Prepare learners to the use of game theory paradigms in the building of more advanced decision support models or systems.


  1. Elements of a game
  2. Categories of games
  3. The extensive form of a game
  4. Information and strategies
  5. Deciding under uncertainty
  6. Randomizing actions; mixed strategies
  7. Game in normal form
  8. Two-player Zero-sum games
  9. Min-Max strategies and Saddle points
  10. Computation of saddle points
  11. Nonzero-sum games
  12. Nash equilibrium
  13. Concave m-person games with coupled constraints
  14. Computation of Nash equilibria
  15. Correlated equilibria
  16. Games of incomplete information


This introduction to Game theory is designed as a sequence of exercises in Applied Mathematics. These exercises permit the learner to grasp the meaning of the main concepts of noncooperative game theory through a series ofhands-on exercises implementing a learning-by-doing cognitive apprenticeship method.

Course material:

  • A textbook (pdf);
  • A set of excel-based exercises;
  • A set of interactive animations;
  • A set of quizzes;
  • An access to distance treatment of advanced optimization codes;
  • Forums to discuss course content;
  • Chat periods to exchange in live sessions.